Title:
Understanding the Development and Implementation of Heuristics and Biases in Design

dc.contributor.advisor Fu, Katherine
dc.contributor.author Fillingim, Kenton Blane
dc.contributor.committeeMember Paredis, Chris
dc.contributor.committeeMember Linsey, Julie
dc.contributor.committeeMember Saldana, Chris
dc.contributor.committeeMember Kurfess, Tom
dc.contributor.department Mechanical Engineering
dc.date.accessioned 2022-08-25T13:30:47Z
dc.date.available 2022-08-25T13:30:47Z
dc.date.created 2021-08
dc.date.issued 2021-08-04
dc.date.submitted August 2021
dc.date.updated 2022-08-25T13:30:48Z
dc.description.abstract Heuristics are rules of thumb used by designers to save time and resources in exchange for satisfactory, but not necessarily optimal, solutions. However, there is a large knowledge gap in understanding how heuristics are developed, retrieved, employed, and modified by designers. Having a better awareness of one’s own set of heuristics can be beneficial for relaying to other team members, improving a team’s training processes, and aiding others on their path to design expertise. Similarly, awareness of heuristics used by other team members could aid a designer’s understanding of decisions outside of their own expertise and the collective vision for the team’s final design. Ultimately, describing how heuristics are used may lead to a more normative approach to heuristics, through determining how one heuristic may add more value to the design process over another. This justification should lead to more effective decision making in design. To do this, the heuristics and their characteristics must be extracted using a repeatable scientific research methodology. This dissertation presents four exploratory case studies aimed at identifying improvements to heuristic extraction methodology, with participants ranging from space mission concept design, advanced manufacturing, and graduate student design teams. A framework for documenting and updating heuristic knowledge over time is formed based on statistically significant correlations of heuristic attributes, specifically in regards to how often a heuristic is used, how the reliable the heuristic is perceived, and how often the heuristic evolves. Lastly, an alternate perspective of heuristics as an error management bias is highlighted and discussed.
dc.description.degree Ph.D.
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/67171
dc.language.iso en_US
dc.publisher Georgia Institute of Technology
dc.subject Heuristics
dc.subject Design
dc.title Understanding the Development and Implementation of Heuristics and Biases in Design
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.advisor Fu, Katherine
local.contributor.corporatename George W. Woodruff School of Mechanical Engineering
local.contributor.corporatename College of Engineering
relation.isAdvisorOfPublication ebcbc0bb-bdfa-4173-b96f-757ab82cd90c
relation.isOrgUnitOfPublication c01ff908-c25f-439b-bf10-a074ed886bb7
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
thesis.degree.level Doctoral
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